空间宇航员个性化对策评估框架

Jennifer Yeung, C. McGregor
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引用次数: 0

摘要

在目前为期4至11个月的国际空间站太空任务中,预防措施和对策演习在维持宇航员的生理健康、福祉和表现方面发挥着不可或缺的作用。虽然这些活动有助于身体适应太空飞行的不利影响,并最大限度地减少与失重相关的身体条件下降的风险,但这些活动不适用于诸如2-3年往返火星的长途旅行。此外,一些从太空任务返回的宇航员仍然存在身体恢复和其他问题,如视力损害、颅内压(VIIP)综合征。如果在适当的时间不采取适当的干预措施,再加上空间隔离和禁闭的影响,宇航员的状况和表现在返回地球后可能会受到很大程度的损害,并对他们的健康和福祉产生长期影响。研究表明,在活跃用户活动期间向其提供相关数据已被证明是有效的,可使他们采取适当的干预措施,以减轻预计的健康风险。目前在国际空间站上的生理数据和对抗设备数据有可能与每名宇航员各自进行的活动相关联,以便采用个性化的生理监测方法进行实时健康评估。本文提出了一种关联方法,利用消防员模拟极端环境研讨会期间收集的大数据作为模拟,实现个性化对策评估。McGregor创建的在线健康分析平台Artemis利用其知识发现的时间抽象、疾病早期检测机制和持续实时监测的能力,展示了这种方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Individualized Countermeasure Assessment Framework for Astronauts in Space
Preventive measures and countermeasure exercises play integral roles in maintaining the physiological health, wellbeing, and performance of astronauts in current day four to 11 month space missions to the ISS. While these activities help the body adapt to the adverse effects of spaceflight and minimize risks of physical deconditioning associated with weightlessness, these activities are inadequate for longer trips such as a 2–3 year mission to and from Mars. Furthermore, physical reconditioning and other issues such as visual impairment intracranial pressure (VIIP) syndrome remain for some astronauts returning from space missions. Combined with the effects of isolation and confinement in space, an astronaut's condition and performance can be compromised to a high degree with long-term impacts to their health and wellness upon returning to Earth if the appropriate interventions are not performed at appropriate times. Research has shown that representation of the relevant data to the active user during their activities has been proven effective in allowing them to perform the appropriate intervention to mitigate projected health risks. The physiological data and countermeasure equipment data currently located on the ISS has the potential to be correlated with the respective activities performed per astronaut for an individualized physiological monitoring approach for real-time health assessments. This paper presents a correlation method to enable individualized countermeasure assessments using big data collected during a simulated extreme environment workshop for firefighters as an analog. The online health analytics platform, created by McGregor, known as Artemis demonstrates this method using its capabilities in temporal abstraction for knowledge discovery, mechanisms for early detection of illnesses, and continuous real-time monitoring.
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